Paper Title:
Sensor Fusion Based on Strong Tracking Filter for Augmented Reality Registration
  Abstract

Accurate tracking for Augmented Reality applications is a challenging task. Multi-sensors hybrid tracking generally provide more stable than the effect of the single visual tracking. This paper presents a new tightly-coupled hybrid tracking approach combining vision-based systems with inertial sensor. Based on multi-frequency sampling theory in the measurement data synchronization, a strong tracking filter (STF) is used to smooth sensor data and estimate position and orientation. Through adding time-varying fading factor to adaptively adjust the prediction error covariance of filter, this method improves the performance of tracking for fast moving targets. Experimental results show the efficiency and robustness of this proposed approach.

  Info
Periodical
Key Engineering Materials (Volumes 467-469)
Edited by
Dehuai Zeng
Pages
108-113
DOI
10.4028/www.scientific.net/KEM.467-469.108
Citation
X. Y. Li, D. Y. Chen, "Sensor Fusion Based on Strong Tracking Filter for Augmented Reality Registration", Key Engineering Materials, Vols. 467-469, pp. 108-113, 2011
Online since
February 2011
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Price
$32.00
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